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to automatically deduce equations that link the input drivers to the system output from input-output data. The field of system identification has developed tools for deriving such mathematical models from data. A
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Background: A strong STEM degree (e.g., engineering, physics, chemistry, materials science, computer science, mathematics) or equivalent experience demonstrating a robust understanding of scientific principles
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(s) assessed at Bachelor’s or master’s degree in Computer Science, Engineering, Applied Mathematics, Data Science, or a related area (or equivalent experience). Essential Application Ability to work
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apply. Criteria Essential or desirable Stage(s) assessed at Five GCSEs at Grade C or above including Mathematics and English (or equivalent experience) Essential Application Prior experience
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the desired behaviour of these infinite-dimensional systems with limited sensing and actuating capabilities—a task that demands cutting-edge mathematical tools and innovative engineering strategies. This PhD
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Data Driven Modelling, Machine Learning, Applied Mathematics/ Statistics, or related engineering and computing fields (or have equivalent experience) Essential Application Strong background in data
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Application/interview Ability to manage and evaluate scientific, mathematical or other technical data/documentation and call attention to any anomaly Essential Application/interview Be able to communicate
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strong mathematical skills in Engineering, Physics, Mathematics or similar discipline. If English is not your first language then you must have an International English Language Testing System (IELTS
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your application. The candidate will require a good first degree with strong mathematical skills in Engineering, Physics, Mathematics or similar discipline. If English is not your first language then you
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, Physics, Mathematics, Engineering, or a related field. Applicants from other backgrounds with strong quantitative, programming, or analytical experience are also encouraged to apply. Strong programming